Advanced Controls for Intelligent Buildings - Goyal, Siddharth

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Auteur(s) : Goyal, Siddharth

Editeur : Crc Press

Langue : Anglais

Parution : 01/07/2021

Format : Moyen, de 350g à 1kg

Nombre de pages : 272

Expédition : 386

Dimensions : 23.4 x 15.6 x 1.5

ISBN : 1032009675

Résumé :
The book focuses on technical and business aspects needed to select, design, develop and deploy control application successfully for multiple components in building systems. It provides guidance on developing an end-to-end system in relation to business fundamentals (distribution channels, marketing, supply-chain and financial management)....

Biographie:

Dr. Siddharth Goyal is currently working as the Director of Data Science Team at Divisions Maintenance Group (DMG). His professional experience ranges from research to product development, product management, strategy, technical leadership, and cross-functional team management. Previous experience includes key positions at LG Electronics, Johnson Controls, Pacific Northwest National Laboratory, University of Florida, National University of Singapore, Indian Institute of Science, Reliance Energy, and GE Motors. He has worked in multiple domains such as energy systems, intelligent buildings, software applications, artificial intelligence, aircraft and satellites, power plants, and robotics. In the past decade, his focus is tackling business challenges through technology in the smart buildings industry.

Dr. Goyal holds a Ph.D. and an M.Sc. in Mechanical Engineering from the University of Florida, and a B.E. in Electrical Engineering from Punjab Engineering College. He has published numerous peer-reviewed papers in international conferences and journals. He has also submitted more than half a dozen patents on multiple new technologies and applications in the industry.

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Sommaire:

1 Building Systems

1.1 Introduction and Motivation

1.2 Building Types

1.2.1 Residential

1.2.2 Commercial

1.3 Building Systems

1.3.1 Overview: System Components and Functionality

1.3.2 HVAC Systems

1.3.2.1 AHU Systems

1.3.2.2 In-room Terminal Units

1.3.2.3 Heat Pumps

1.3.2.4 VRF (Variable Refrigerant Flow) Systems

1.4 Control System Architecture

1.5 Moving toward the Future: Smart/Intelligent Buildings

2 Sensing

2.1 Background and Overview

2.1.1 Characteristics

2.1.2 Analog vs. Digital

2.2 Virtual Sensors

2.2.1 Analytical

2.2.2 Empirical

2.3 Sensors Types and Availability in Buildings

2.3.1 Temperature Sensors

2.3.2 Pressure Sensors

2.3.3 Flow Rate Sensors

2.3.4 Speed Sensor

2.3.5 Electrical Sensors

2.3.6 Humidity Sensors

2.3.7 Light Sensors

2.3.8 Occupancy/Motion Sensors

2.3.9 Security Sensors

2.3.10 Air Quality Sensors

2.3.11 Outdoor Environmental Sensors

2.3.12 Position Sensors

2.3.13 Safety Sensors

2.3.14 Meters or Usage Sensors

2.3.15 Tracking Sensors

2.3.16 Other Sensors

3 Modeling

3.1 Modeling Approaches

3.1.1 White Box

3.1.2 Black Box

3.1.3 Grey Box

3.2 Modeling Process

3.2.1 Model Types

3.2.2 Order Reduction and Approximation

3.2.3 Calibration and Validation

3.3 Components and Systems

3.3.1 Fan

3.3.2 Chiller

3.3.3 Heat Exchanger

3.3.4 Pump

3.3.5 Damper

3.3.6 Thermal Models

3.3.7 Moisture and Humidity

3.3.8 Simulation Tools

3.4 Model Selection

4 Control

4.1 Control Product Types

4.2 Value of Control in Buildings

4.3 Control Approach

4.3.1 Centralized

4.3.2 Decentralized

4.3.3 Distributed

4.3.4 Hierarchical

4.3.4.1 Supervisory Control (SC)

4.4 Control Algorithms/Strategies

4.4.1 Bang-bang Control

4.4.2 Rule/Event-based Control

4.4.3 Finite State Machine (FSM)

4.4.4 PID (Proportional-integral-derivative) Control

4.4.5 Model Predictive Control (MPC)

4.4.6 Adaptive Control

4.4.6.1 Parameter Tuning

4.4.6.2 Reference Tuning

4.4.7 Economic control

4.4.8 Miscellaneous

4.5 Optimal Selection of Controls

5 Testing and Deployment

5.1 Test Bed Design

5.1.1 Simulation

5.1.2 Hardware-in-loop (HIL)

5.1.2.1 Controller-in-loop (CIL)

5.1.2.2 Equipment-in-loop (EIL)

5.1.3 Laboratory Testing

5.1.4 Field Demonstration

5.2 Product vs. Prototype vs. POC

5.3 Testing Methodology

5.3.1 Module-level

5.3.2 System-level

5.3.3 Feature-level

5.3.4 Other testing

5.4 Validation Mechanism

5.4.1 Eye-ball

5.4.2 Semi-automated

5.4.3 Fully-automated

5.5 Validation Criteria

5.6 Creating a Powerful Testing Infrastructure

5.7 Deployment

5.7.1 Packaging

5.7.2 Installation

5.7.3 Automatic Binding

5.7.4 Tracking

5.7.5 Update and Maintain

6 Control Use Cases, Artificial Intelligence, and Internet of

Things

6.1 Control Use Cases

6.1.1 Precooling and Preheating

6.1.2 Ice/Cold-water Storage System

6.1.3 Duct Static Pressure Reset

6.1.4 Optimal Start/Stop

6.1.5 Night Purge Ventilation

6.1.6 Demand Control Ventilation (DCV)

6.1.7 Temperature Setback

6.1.7.1 Domestic Hot Water Temperature Reset

6.1.7.2 Zone Temperature Reset

6.1.7.3 SA Temperature Reset

6.1.7.4 Refrigeratio...